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Record W7161990477 · doi:10.82308/41645

Implementing a positive behavior support program: a teacher-researcher study

2013· dissertation· en· W7161990477 on OpenAlexaboutno aff
Victoria Zilberman

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Process (computing)Behavior managementData collectionPositive behavior supportField (mathematics)Behavior changeLearning environment

Abstract

fetched live from OpenAlex

The academic success of students depends, among several factors, on the school's learning environment and the teacher's classroom management skills. In recent years creative solutions to curb poor behavior by establishing proper class discipline have come to the forefront of the teaching profession. With that in mind, the present research topic was chosen to foster appropriate student conduct in establishing and sustaining a productive learning environment through the use of the Positive Behavior Support model. This teacher-as-researcher study took place over a one-year period (2010-2011) in a secondary two class of twenty-five students at a Quebec high school. The collection of the data by means of daily observations of the whole class and three preselected case students was intended to examine the effectiveness of the methods of behavior management used in the field with the teacher's application of them in the classroom. The research results conclude that the Positive Behavior Approach model contributed to a reduction in the number of incidents of poor behavior and an overall improvement of the learning environment in the class. Furthermore, the study enabled personal growth in teaching philosophy, style and enrichment of pedagogical methods and techniques through a process of reflection, analysis and adjustments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.275
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0270.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.482
Teacher spread0.424 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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